Model Context Protocol (MCP) and A2A for Smarter AI Agents

Name: Model Context Protocol (MCP) and A2A for Smarter AI Agents
Rating: 4.8 (28 reviews)

Learn Model Context Protocol (MCP) and Agent to Agent (A2A) Protocol an Skills to Build Powerful AI Systems

Created byAref Karimi

Last updated 5/2026

English

What you'll learn

Understand the fundamentals of MCP and ACP and their roles in AI systems
Learn to implement MCP for managing model context in AI workflows
Master ACP for enabling efficient communication between AI agents
Build practical projects using MCP and ACP in simulated environments
Explore best practices for designing scalable and secure AI communication systems

Course content

10 sections • 44 lectures • 3h 40m total length

Introduction5:24
What is an AI Agent3:27
What is an AI Agent, and how is it different to a normal agent? Large Language Models have given the power of reasoning, prediction and conversation to the classic agents. With AI-powered agents, your legacy systems that had to hard-code everything, to use human-like conversations to get the job done.
What is MCP2:19
MCP is a relatively new concept. AI-agents use Large Language Models (LLMs) to respond to human-like requests or prompts. LLMs do not have any access to your organisational or personal data. They do not even know what day it is! MCPs find the external resources and information and bring them to the LLM so that they can provide you with context-aware responses. MCP is a protocol because it provides a unified and universal interface to all MCP servers.
What is Agent to Agent Protocol (A2A)5:36

Demonstration of Weather MCP in Claude Desktop1:53
In this lecture you wil see that how an MCP server called "Weather MCP" can be downloaded from the Interenet, and be integrated with your Claude Desktop application, providing the capability of forecasting the weather to Claude!
MCP Architecture : The Host2:59
Model Context Protocol (MCP) follows a specific architecture called host-client-server. This lecture is about the overal architecture and the role of Host.
MCP Architecture: The Client1:34
Model Context Protocol (MCP) follows a specific architecture called host-client-server. This lecture is about the overal architecture and the role of Client.
MCP Architecture: The Server1:50
Model Context Protocol (MCP) follows a specific architecture called host-client-server. This lecture is about the overal architecture and the role of Server.
The Underlaying Protocols of MCP2:54
MCP servers can run locally or remotely. Depending how they are deployed, you will access them using a different protocol. It is crucial to know what protocols exist and when you use them.
MCP in Action with Claude Desktop6:51
Let's download a MCP server that is written in Python and plug it into Claude Desktop!

Setting Up Your Coding Environment3:03
Exciting! It is time to code our own Model Context Protocol. In this course we will use Python. In this lecture we will prepare our Python environment and install the required librarires. We will also learn what othe programming languages are supported by the MCP SDK.
Coding an MCP Server Tool with Python5:38
MCP servers can be Tools, Resources or Prompts. In this lecture we learn how we code a Tool server.
Coding MCP Server Resource with Python4:14
MCP servers can be Tools, Resources or Prompts. In this lecture we learn how we code a Resource server.
Coding MCP Server Prompt with Python3:44
MCP servers can be Tools, Resources or Prompts. In this lecture we learn how we code a Prompt server.
Loading MCP Server into Claude Desktop3:35
We coded a personalised greeting produce MCP server. Let's plug it into Claude Desktop and use it!
Streamable HTTP Transport in MCP Servers8:17
MCP Servers can be deployed remotely. You will use Streamable HTTP Transport protocol to access remote MCP servers. In this lecture we will see that in action.
Production-grade Deployment and Stateful MCP Servers7:42
When we delploy distributed MCP servers for production-grade use, we must take several aspects into account, including scalability and security.
Developing MCP Clients6:45
In most cases, an AI Agent framework such as Lang Chain and BEE AI can utilise MCP servers without needing us to write custom code. But if you need to write a custom client to access an MCP server, you can watch this lecture and learn how to do it!
Securing HTTP MCP Servers and Clients with Open Authetnication (OAuth)13:14
Remote MCP Servers that are accessed via HTTP must be protoceted against unauthorised users. This lecture explains how you can leverage the power of Open Authentication (OAuth) 2.0, and Auth0, to protect your MCP servers.
Sampling in MCP10:43

Introduction - What is MCP?2:38
Benefits of Adopting MCP2:25
Strategies to Implement MCP5:40
If, as a technology leader, you want to roll out MCP in your organisation, you must follow a strategic plan to successfully onboard all key stakeholders, meet compliance requirements, build capabilities and organise teams. In this leacture you will be presented with a 4-phase strategy to do so.
Governance, Security, and Future-Proofing Your MCP Investment4:06
Assignment: Develop a Framework for Adopting MCP0:56

Requirements

Basic understanding of AI and machine learning concepts
Familiarity with Python Programming
Knowledge of Networking Basics (e.g., APIs, sockets)

Description

Artificial Intelligence took a major leap with the rise of Large Language Models like ChatGPT. However, building truly intelligent AI systems goes far beyond having a conversation with an AI assistant such as ChatGPT. Modern AI applications rely on multiple autonomous AI agents that require shared context, coordination, and collaboration.

This is where Model Context Protocol (MCP) and Agent to Agent Protocol (A2A) become essential. Model Context Protocol enables AI agents to access structured, real-time context from external tools, services, and data sources, ensuring decisions are made with accurate and relevant information. Agent to Agent Protocol focuses on how multiple AI agents communicate, delegate tasks, and work together as a coordinated system rather than operating in isolation.

In this course, you will learn how MCP and A2A are used together to design smarter, interoperable AI systems. You will explore how these protocols fit into modern AI architectures and how they enable scalable multi-agent workflows built on top of Large Language Models.

The course combines clear conceptual explanations with practical, hands-on examples. Developers will implement Model Context Protocol and Agent to Agent interactions using Python and widely used SDKs. The course concludes with a SIM activation project, where you will build a website backed by an AI workflow that allows telco customers to activate their SIM cards.

If you are less hands-on, such as a leader, solution architect, or product manager, there is a dedicated section designed for non-technical roles. You will gain a solid understanding of how MCP tools, Skills and A2A support real-world AI applications and how they apply in business contexts.

By the end of the course, you will be able to build AI systems that maintain context, collaborate across agents, and adapt intelligently to changing requirements. This course is suitable for all proficiency levels and equips you with both strategic insight and practical skills for modern AI development.

Who this course is for:

AI developers and machine learning engineers
Data scientists interested in AI system integration
System architects designing agent-based AI solutions
Intermediate to advanced learners with basic knowledge of AI, Python, and networking concepts

Model Context Protocol (MCP) and A2A for Smarter AI Agents

What you'll learn

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Course content

Introduction4 lectures • 17min

Deep Dive into Model Context Protocol (MCP)6 lectures • 18min

Coding MCP Servers and Clients for Developers10 lectures • 1hr 7min

MCP Gateways1 lecture • 4min

Exploring Agent to Agent (A2A) Protocol7 lectures • 58min

Deploying A2A Agents to Production Environments4 lectures • 18min

MCP for Leaders and Business Professionals5 lectures • 16min

Architecting AI Agent Skills1 lecture • 4min

Workshop - SIM Activation Chat Bot5 lectures • 17min

Course Wrap-Up1 lecture • 2min

Requirements

Description

Who this course is for: